A resource-constrained-based assembly process flow planning method

Abstract

The present application relates to a kind of based on resource constraint assembly process flow planning method, it solves the current mode to production information collection, analysis requirement high, inefficient, scheduling cycle is long, response is slow, and it does not have foresight, the problem of lag assembly process.It includes the following steps: step 1: resource statistics;Step 2: process carding;1) carding each process required resource;2) carding each process required time;3) carding the absolute time sequence between process, and draw flow chart according to shortest time logic;Step 3: station content design;Step 4: system building;Step 5: digital simulation;Step 6: data collection and feedback;Step 7: bottleneck resource reserve;Step 8: iteration update;Step 9: system scheduling.The present application reduces the waiting time caused by production resource limitation, makes the existing resource play to the maximum effect, can effectively improve production efficiency, realizes assembly process flow planning based on resource constraint.

Description

Technical Field

[0001] This invention belongs to the field of final assembly process planning, and specifically relates to a final assembly process planning method based on resource constraints. Background Technology

[0002] Final assembly is the final stage of manufacturing, and its smooth progress directly impacts product delivery on time. However, in actual production, resource shortages frequently hinder the overall progress of final assembly. Currently, final assembly plants typically address resource constraints by manually and temporarily adjusting production plans and resource allocation through scheduling systems. This approach requires sophisticated production information collection and analysis, is inefficient, has long scheduling cycles, slow response times, lacks foresight, and delays the final assembly process. Therefore, proposing a resource-constrained final assembly process planning method is essential. Summary of the Invention

[0003] This invention designs a resource-constrained final assembly process planning method, which solves the problems of the current model, such as high requirements for production information collection and analysis, low efficiency, long scheduling cycle, slow response, lack of foresight, and lag in the final assembly process.

[0004] This invention is achieved through the following technical solutions:

[0005] A resource-constrained final assembly process planning method includes the following steps:

[0006] Step 1: Resource Statistics:

[0007] Organize the existing production resources in the workshop, including workers, tooling, standard parts, components, finished products, tools, and testing equipment;

[0008] Step 2: Process Flowchart

[0009] 1) Identify the resources required for each process, including workers, tooling, standard parts, components, finished products, tools, and testing equipment;

[0010] 2) Analyze the time required for each process;

[0011] 3) Analyze the absolute time sequence between processes and draw a flowchart based on the shortest time logic;

[0012] The process of drawing a flowchart based on the shortest time logic is to organize the process logic diagram with the most parallel processes and the fewest intersections.

[0013] Step 3: Workstation Content Design:

[0014] Based on the information compiled in step 2, rationally plan the work content of each workstation, and try to ensure that the working time and production resources occupied by each workstation are relatively average.

[0015] Step 4: System Setup

[0016] The production resources counted in step 1, the process information in step 2, and the workstation information in step 3 are digitized and uploaded to the scheduling system.

[0017] The scheduling system should also be able to identify and classify the status of existing resources in real time, including: in use and expected usage time, idle, fault and recovery time, etc.

[0018] Step 5: Digital Simulation

[0019] Based on the process logic in step 2, combined with the production resources in step 1, and using the scheduling system built in step 4, the process logic sorted out in step 3 is simulated under the premise of existing production resources to verify whether the workstation content design in step 3 is reasonable. Based on the simulation results, the process logic and workstation content are optimized under the existing resource constraints.

[0020] Step 6: Data Collection and Feedback

[0021] Based on the optimal process logic and workstation distribution optimized in step 5, a trial run was conducted in the workshop. During the trial run, production data was collected, including the actual time taken for each process, the actual usage time of each tool, fixture, and equipment, the number of available spaces at the same time, the actual working time of each workstation, and worker feedback on the process, workstation, and production data.

[0022] Step 7: Bottleneck Resource Reserves:

[0023] Based on the information collected in step 6 and the feedback from workers, identify the bottlenecks restricting the final assembly process, including tooling, equipment, and parts, prepare backups in advance, and develop contingency plans.

[0024] Based on the identified bottlenecks restricting the final assembly process, the process logic was adjusted again to avoid processes using the same scarce resources.

[0025] Step 8: Iterative Update: Update the trial operation data obtained in Step 6 and the production data supplemented in Step 7 into the system built in Step 4, and perform Step 5 again to iteratively optimize the final assembly process to obtain the optimal solution.

[0026] Step 9: System Scheduling: Run the optimal solution iterated in Step 8, and use the system built in Step 4 to perform real-time digital monitoring of the entire assembly process. Based on the real-time production resource situation, simulate subsequent processes in advance, identify production resource shortages in advance, automatically provide prompts based on the resources required for subsequent processes identified in Step 2, and redistribute assembly resources and replan the process flow in combination with the existing resource status of the workshop as statistically analyzed in Step 4.

[0027] This invention dynamically adjusts the sequence of assembly processes through a scheduling system, reducing waiting time caused by limited production resources, maximizing the use of existing resources, effectively improving production efficiency, and realizing assembly process planning based on resource constraints. Attached Figure Description

[0028] Figure 1 This invention provides a flowchart for planning the final assembly process based on resource constraints. Detailed Implementation

[0029] To better understand the specific implementation process of this achievement, further explanation is provided below in conjunction with actual production practices and accompanying diagrams.

[0030] like Figure 1 As shown, this invention is a resource-constrained assembly process planning method, and the specific steps are as follows:

[0031] Step 1: Assess the current production data in the workshop, such as the types and number of workers, the jobs they can do, the number and range of torque wrenches, the specifications and number of screwdrivers, the range and number of vernier calipers, the specifications and number of standard parts, the types and number of tooling, the number of equipment, and whether it can operate normally, etc.

[0032] Step 2: Determine the number of personnel required for each process, the specifications and quantity of tooling and fixtures, the time required for each process, the absolute time logic sequence between processes, and compile a process logic diagram with the most parallel processes and the fewest intersections.

[0033] Step 3: Based on the logic and time between processes compiled in Step 2, reasonably arrange the workstation content under the existing resource constraints, so that the working time of each workstation is as consistent as possible, and avoid a certain workstation occupying a certain production resource for too long, thus restricting the overall assembly progress.

[0034] Step 4: Digitize the information from Steps 1 to 3 and input it into the scheduling system for real-time monitoring, which will facilitate subsequent digital simulation, process iteration and system scheduling.

[0035] Step 5: Based on the existing resources identified in Step 1, verify the process in Step 2 and the workstation content in Step 3, determine their rationality, and optimize them based on the simulation results.

[0036] Step 6: Implement the optimal solution simulated in Step 5, and collect various data generated during the production process in real time, such as the actual time taken for each process, the actual time occupied by tooling and fixtures, etc. In addition, pay attention to collecting feedback from workers on process logic and workstation distribution.

[0037] Step 7: Based on actual operational conditions, identify the bottlenecks currently hindering the entire assembly process, such as specific tools, fixtures, or equipment. For production resources in short supply, prepare inventory in advance or enhance maintenance to ensure the bottleneck resources operate at their maximum capacity. Based on the identified resource shortages, readjust the process logic to avoid processes using the same scarce resource.

[0038] Step 8: Add the data obtained in Step 6 and Step 7 to the scheduling system, and repeat Step 5 to iteratively optimize the process flow and obtain the optimal process under resource-constrained conditions.

[0039] Step 9: Implement the optimal process iterated in Step 8, monitor the operation of equipment, tooling, tools, personnel and other production materials at the workstations in real time. If any problems or occupancy occur, the scheduling system will provide advance warnings and dynamically adjust the final assembly process based on the currently available production materials to ensure the smooth progress of the final assembly process.

[0040] This invention can dynamically, automatically, quickly, and proactively reallocate production resources based on subsequent production processes and replan the final assembly process flow in response to different resource constraints. This can greatly improve the utilization rate of production resources, increase production efficiency, and realize the planning of the final assembly process flow under resource constraints.

Claims

1. A resource-constrained final assembly process planning method, characterized by: Includes the following steps: Step 1: Resource Statistics: Analyze the existing production resources in the workshop; Step 2: Process Flowchart 1) Analyze the resources required for each process; 2) Analyze the time required for each process; 3) Analyze the absolute time sequence between processes and draw a flowchart based on the shortest time logic; Step 3: Workstation Content Design: Based on the information compiled in step 2, rationally plan the work content of each workstation to ensure that the working time and production resources occupied by each workstation are relatively evenly distributed. Step 4: System Setup The production resources counted in step 1, the process information in step 2, and the workstation information in step 3 are digitized and uploaded to the scheduling system; the scheduling system enables real-time identification and classification of the status of existing resources. Step 5: Digital Simulation Based on the process logic in step 2, combined with the production resources in step 1, and using the scheduling system built in step 4, the process logic sorted out in step 3 is simulated under the premise of existing production resources to verify whether the workstation content design in step 3 is reasonable. Based on the simulation results, the process logic and workstation content are optimized under the existing resource constraints. Step 6: Data Collection and Feedback Based on the optimal process logic and workstation distribution optimized in step 5, a trial run was conducted in the workshop. During the trial run, production data was collected, including the actual time taken for each process, the actual usage time of each tool, fixture, and equipment and the number of available slots at the same time, the actual working time of each workstation, and workers' suggestions for improvement on the process, workstation, and production data. Step 7: Bottleneck Resource Reserves: Based on the information collected in step 6 and the feedback from workers, identify the bottlenecks restricting the final assembly process, including tooling, equipment, and parts, prepare backups in advance, and develop contingency plans. Step 8: Iterative Update: Update the trial operation data obtained in Step 6 and the production data supplemented in Step 7 into the system built in Step 4, and perform Step 5 again to iteratively optimize the final assembly process to obtain the optimal solution. Step 9: System Scheduling: Run the optimal solution iterated in Step 8, and use the system built in Step 4 to perform real-time digital monitoring of the entire assembly process. Based on the real-time production resource situation, simulate subsequent processes in advance, identify production resource shortages in advance, automatically provide prompts based on the resources required for subsequent processes identified in Step 2, and redistribute assembly resources and replan the process flow in combination with the existing resource status of the workshop as statistically analyzed in Step 4.

2. The assembly process planning method based on resource constraints according to claim 1, characterized in that: In step 1, the existing production resources in the workshop that are identified include workers, tooling, standard parts, components, finished products, tools, and testing equipment.

3. The method for planning the final assembly process based on resource constraints according to claim 1, characterized in that: In step 2, the resources required for each process include workers, tooling, standard parts, components, finished products, tools, and testing equipment.

4. The method for planning the final assembly process based on resource constraints according to claim 1, characterized in that: In step 2, drawing the flowchart according to the shortest time logic involves organizing the process logic diagram with the most parallel processes and the fewest intersections.

5. The method for planning the final assembly process based on resource constraints according to claim 1, characterized in that: In step 4, when the scheduling system identifies and classifies the status of existing resources in real time, the status includes: in use and expected usage time, idle, fault and recovery time.

6. The method for planning a final assembly process based on resource constraints according to claim 1, characterized in that: In step 7, based on the identified bottlenecks restricting the final assembly process, the process logic is adjusted again to avoid processes using the same scarce resources.

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